Agentic AI workflows fail without classified first-party data. Venkata Pagadala, AI Product Manager for Search at AT&T, classified 5.8 million queries, removed 3 million noise queries, and uses the resulting persona-based insights to build mockups that win leadership buy-in. He outlines a competitor-navigation and Wikipedia-driven L1/L2/L3 taxonomy that surfaces zero-search-volume, high-intent demand from Reddit, Quora, and YouTube, plus a UGC-based research framework that treats reviews, ratings, and brand response rates as primary inputs. He also covers persona-based query fan-outs as a replacement for single-prompt tracking, and documentation systems that let AI agents repeat classification at scale.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Rss Apple Podcaster
Podden och tillhörande omslagsbild på den här sidan tillhör I Hear Everything. Innehållet i podden är skapat av I Hear Everything och inte av, eller tillsammans med, Poddtoppen.